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I guess sending configurations is not that difficult.
We can write configs (as `Map[String, String]` for further configurations
in the future?) before `PythonUDFRunner.writeUDFs(dataOut, funcs, ar
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Yup, my impression was that there could be a corner case too but I wasn't
sure how much the corner case makes sense, and haven't checked it closelt yet.
I believe elaborating the case might be h
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Github user ueshin commented on the issue:
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I'm sorry for the late review, but I think the current fix is still
behavior change..
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Retest this please
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So, one thing that I was thinking about is whether it would be worth it to
make error handling a little better here. I think this is no worse than the
current status quo, and looking at the related P
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--- Diff: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala ---
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}
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}
/**
-
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Github user vanzin commented on the issue:
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This doesn't seem to be addressing the issue reported in the bug. The exact
same error happens with your patch:
```
$ ./bin/run-example
Exception in thread "main" java.lang.IllegalAr
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Github user tgravescs commented on the issue:
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+1 pending sparkQa, changes look good, and I manually verified against both
the jira use cases.
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IIUC this PR print the config key in the error message if the config
value(either default or get from the configMap) can't be cast properly.
Personally I think it add some value to include this
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Cloneable with Lo
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Cloneable with L
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[SPARK-24414][ui] Calculate the correct number of tasks for a stage.
This change takes into account all non-pending tasks when calculating
the number of tasks to be shown. This also means that wh
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Here is the issue in Scala side. https://github.com/scala/bug/issues/10913
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Github user dbtsai commented on the issue:
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I'm also looking at this issue. The challenge is that one of the hacks we
use to initialize the Spark
before REPL sees any files was removed in Scala 2.11.12.
https://github.com/apache/s
Github user daniel-shields commented on the issue:
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This case can also occur when the datasets are different but share a common
lineage. Consider the following:
`df = spark.range(10)
df1 = df.groupby('id').count()
df2 = df.groupby('
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@jerryshao can you review this minor update ?
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Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/20697#discussion_r191567638
--- Diff:
resource-managers/kubernetes/integration-tests/src/test/scala/org/apache/spark/deploy/k8s/integrationtest/backend/IntegrationTestBackend.scala
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Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/20697#discussion_r191568423
--- Diff:
resource-managers/kubernetes/integration-tests/scripts/setup-integration-test-env.sh
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+#!/usr/bin/env bash
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+#
Github user SparkQA commented on the issue:
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Github user SparkQA commented on the issue:
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Github user mgaido91 commented on the issue:
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@daniel-shields in that case you have 2 different datasets `df1` and `df2`.
So they are 2 distinct attributes and the check `a.sameRef(b)` would return
false. This is applied only in case you have
Github user mgaido91 commented on the issue:
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@juliuszsompolski yes, you're right, sorry, SPARK-24395 uses literal and
not subqueries, sorry.
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Github user gaborgsomogyi commented on the issue:
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